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Research

My primary research areas include computational neuroscience, mathematical statistics, data analysis, and deep learning. Currently, my work is focused on inferring connections in small to medium-sized neuronal network models, analyzing neural data recordings, developing novel generators for statistical distributions, devising estimation techniques for statistical distribution parameters, and exploring the integration of deep learning into neural network applications.

For more information about our research and team, please read the CSDA (Computational Statistics and Data Analytics) Lab: https://csdalab.github.io/

Highlights

Computational 

Neuroscience

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Analysis for Neuron Recordings

Statistic Distributions

Neural Network
Connectivity

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Deep Learning and Neural Network Models

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Selected Publications

Posters

Recent posters have been displayed on the wall outside my office. For additional details, read the "Publications" section on the CSDA website via the following link.

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